Impact of predictive model-directed end-of-life counseling for Medicare beneficiaries.

Objectives: To validate a predictive model for identifying Medicare beneficiaries who need end-of-life care planning and to determine the impact on cost and hospice care of a telephonic counseling program utilizing this predictive model in 2 Medicare Health Support (MHS) pilots.

Study Design: Secondary analysis of data from 2 MHS pilot programs that used a randomized controlled design.

Methods: A predictive model was developed using intervention group data (N = 43,497) to identify individuals at greatest risk of death.

Effectiveness of disease management programs on improving diabetes care for individuals in health-disparate areas.

In addition to race and ethnicity, specific geographic regions are associated with poorer outcomes of care. Individuals with diabetes experiencing health disparities typically have worse long-term outcomes, such as increased diabetes complications and mortality. Zip code mapping, or geocoding, was utilized in this study to identify regions of the United States with high diabetes prevalence rates and to identify areas with high densities of minority populations.